⚙️ adding settings doc

docs/settings.md

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+# Settings
+
+## Settings Class Overview
+
+The configuration settings for Funcchain are encapsulated within the `FuncchainSettings` class. This class inherits from Pydantic's `BaseSettings`.
+
+`funcchain/config.py`
+```python
+class FuncchainSettings(BaseSettings):
+    ...
+```
+
+## Setting Descriptions
+
+### General Settings
+
+- `LLM: BaseChatModel | RunnableWithFallbacks | None = None`
+  Defines the language learning model to be used. It can be a type of `BaseChatModel`, `RunnableWithFallbacks`, or `None`.
+
+- `VERBOSE: bool = True`
+  Enables or disables verbose logging.
+
+### Prompt Settings
+
+- `MAX_TOKENS: int = 4096`
+  Specifies the maximum number of tokens for chat models.
+
+- `DEFAULT_SYSTEM_PROMPT: str = "You are a professional assistant solving tasks."`
+  Default prompt used for initializing the system.
+
+### API Keys
+
+- `OPENAI_API_KEY: Optional[str] = None`
+  API key for the OpenAI service.
+
+- `AZURE_API_KEY: Optional[str] = None`
+  API key for the Azure service.
+
+- `ANTHROPIC_API_KEY: Optional[str] = None`
+  API key for the Anthropic service.
+
+- `GOOGLE_API_KEY: Optional[str] = None`
+  API key for the Google service.
+
+- `JINACHAT_API_KEY: Optional[str] = None`
+  API key for the JinaChat service.
+
+### Azure Settings
+
+- `AZURE_API_BASE: Optional[str] = None`
+  Base URL for the Azure API.
+
+- `AZURE_DEPLOYMENT_NAME: str = "gpt-4"`
+  Deployment name for the Azure service.
+
+- `AZURE_DEPLOYMENT_NAME_LONG: Optional[str] = None`
+  Extended deployment name for the Azure service, if applicable.
+
+- `AZURE_API_VERSION: str = "2023-07-01-preview"`
+  API version for the Azure service.
+
+### Model Keyword Arguments
+
+- `MODEL_NAME: str = "openai::gpt-3.5-turbo"`
+  Name of the language model.
+
+- `MODEL_TEMPERATURE: float = 0.1`
+  Controls the randomness in the model's output.
+
+- `MODEL_REQUEST_TIMEOUT: float = 210`
+  Timeout for the model API request, in seconds.
+
+- `MODEL_VERBOSE: bool = False`
+  Enables or disables verbose logging for the model.
+
+### Additional Methods
+
+- `model_kwargs(self) -> dict[str, Any]`
+  Method that returns a dictionary of keyword arguments for the model initialization based on the settings.